adaptive noise reduction premiere obsolete

'PhaseOffset',phase, 'SamplesPerFrame',512, 'SampleRate',Fs) Sine = audioOscillator( 'NumTones', La, 'Amplitude',A, 'Frequency',F.

Phase = rand(1,La) % Random initial phase % Sine wave generator to synthetically create the noiseĪ = 'SecondaryPathCoefficients',SecondaryPathCoeffsEst) NoiseController = dsp.FilteredXLMSFilter( 'Length',L, 'StepSize',muW. % Filtered-X LMS adaptive filter to control the noise PrimaryPathGenerator = dsp.FIRFilter( 'Numerator',primaryPathCoeffs.') % FIR Filter to be used to model primary propagation path For this active noise control task, we shall use a sampling frequency of 8000 Hz. The following commands generate a loudspeaker-to-error microphone impulse response that is bandlimited to the range 160 - 2000 Hz and with a filter length of 0.1 seconds. The secondary propagation path is the path the anti-noise takes from the output loudspeaker to the error microphone within the quiet zone.

Morgan, 'Active Noise Control Systems: Algorithms and DSP Implementations', Wiley-Interscience, New York, 1996. The active noise control system must take into account the secondary loudspeaker-to-microphone error path in its adaptation.įor more implementation details on active noise control tasks, see S.M. This problem differs from traditional adaptive noise cancellation in that: - The desired response signal cannot be directly measured only the attenuated signal is available. The goal of the active noise control system is to produce an 'anti-noise' that attenuates the unwanted noise in a desired quiet region using an adaptive filter. The noise signal usually comes from some device, such as a rotating machine, so that it is possible to measure the noise near its source.

In active noise control, one attempts to reduce the volume of an unwanted noise propagating through the air using an electro-acoustic system using measurement sensors such as microphones and output actuators such as loudspeakers.

Adaptive noise reduction premiere obsolete